標題: Titlebook: Computational Linguistics and IntelligentText Processing; 20th International C Alexander Gelbukh Conference proceedings 2023 Springer Natur [打印本頁] 作者: DUCT 時間: 2025-3-21 19:23
書目名稱Computational Linguistics and IntelligentText Processing影響因子(影響力)
書目名稱Computational Linguistics and IntelligentText Processing影響因子(影響力)學科排名
書目名稱Computational Linguistics and IntelligentText Processing網絡公開度
書目名稱Computational Linguistics and IntelligentText Processing網絡公開度學科排名
書目名稱Computational Linguistics and IntelligentText Processing被引頻次
書目名稱Computational Linguistics and IntelligentText Processing被引頻次學科排名
書目名稱Computational Linguistics and IntelligentText Processing年度引用
書目名稱Computational Linguistics and IntelligentText Processing年度引用學科排名
書目名稱Computational Linguistics and IntelligentText Processing讀者反饋
書目名稱Computational Linguistics and IntelligentText Processing讀者反饋學科排名
作者: 即席演說 時間: 2025-3-21 23:05 作者: 群居男女 時間: 2025-3-22 02:52 作者: 冒失 時間: 2025-3-22 08:15 作者: exhibit 時間: 2025-3-22 08:42 作者: amphibian 時間: 2025-3-22 14:56
A Hybrid Generative/Discriminative Model for?Rapid Prototyping of?Domain-Specific Named Entity Recoga, and thus permits the iterative and incremental design of named entity (NE) classes for new domains. The proposed model is a hybrid of a generative model named PYHSMM and a semi-Markov CRF-based discriminative model, which play complementary roles in generalizing seed terms and in distinguishing b作者: amphibian 時間: 2025-3-22 17:26 作者: cravat 時間: 2025-3-22 23:47
A Computational Approach to?Measuring the?Semantic Divergence of?Cognatess. Semantic divergence in related languages is a key concern of historical linguistics. In this paper we investigate semantic divergence across languages by measuring the semantic similarity of cognate sets in multiple languages. The method that we propose is based on cross-lingual word embeddings. 作者: 蜈蚣 時間: 2025-3-23 02:21 作者: 極端的正確性 時間: 2025-3-23 08:50 作者: 噴出 時間: 2025-3-23 11:49 作者: Emmenagogue 時間: 2025-3-23 14:07
Fusing Phonetic Features and?Chinese Character Representation for?Sentiment Analysisons. We are the first to argue that these two important properties can play a major role in Chinese sentiment analysis. Hence, we learn phonetic features of Chinese characters and fuse them with their textual and visual features in order to mimic the way humans read and understand Chinese text. Expe作者: GRUEL 時間: 2025-3-23 21:30
Sentiment-Aware Recommendation System for?Healthcare Using Social Mediaeby seeking guidance and interacting with people of the community. The shared content, though informal and unstructured in nature, contains valuable medical and/or health related information and can be leveraged to produce structured suggestions to the common people. In this paper, at first we propo作者: 干旱 時間: 2025-3-23 23:27
Sentiment Analysis Through Finite State Automatand the subjectivity of the user generated contents make the automatic “understanding” of texts extremely hard. Assuming that the semantic orientation of sentences is based on the manipulation of sentiment words, we built from scratch, for the Italian language, a network of local grammars for the ann作者: SPASM 時間: 2025-3-24 03:53 作者: Mast-Cell 時間: 2025-3-24 10:35
Opinion Spam Detection with?Attention-Based LSTM Networksake online reviews, can be detrimental to both customers as well as organizations. Several methods have been proposed to automatically detect fake opinions; however, the majority of these methods focus on feature learning techniques based on a large number of handcrafted features. Deep learning and 作者: nitroglycerin 時間: 2025-3-24 11:53 作者: 盟軍 時間: 2025-3-24 16:02
,Grundzüge turbulenter Str?mungen,ut not sufficient to cover all elements of verb structure. We conducted a statistical analysis of semantic role representation in VerbNet and FrameNet to provide empirical evidence of insufficiency. The consequence of that is a hybrid role-scalar approach.作者: Morsel 時間: 2025-3-24 19:47
https://doi.org/10.1007/978-3-031-24340-0Computer Science; Informatics; Conference Proceedings; Research; Applications作者: Neolithic 時間: 2025-3-24 23:22 作者: output 時間: 2025-3-25 04:55 作者: 流眼淚 時間: 2025-3-25 11:03 作者: Antarctic 時間: 2025-3-25 15:30
https://doi.org/10.1007/978-3-540-38441-0atabases, such as GenBank?[.], however, information provided in these databases are usually limited to the country or state level. More fine-grained localization information requires phylogeographers to manually read relevant scientific articles. In this work we propose an approach to automate the p作者: 燦爛 時間: 2025-3-25 19:49
https://doi.org/10.1007/978-3-540-38441-0raining data that contains annotated named entities. However, it is expensive to construct such training data for low-resource domains. In this paper, we propose a recognizer that uses not only training data but also a domain specific dictionary that is available and easy to use. Our recognizer firs作者: Chagrin 時間: 2025-3-25 23:54 作者: 無禮回復 時間: 2025-3-26 02:47 作者: CYN 時間: 2025-3-26 05:52 作者: 絕種 時間: 2025-3-26 11:25
https://doi.org/10.1007/978-3-540-38441-0s. Semantic divergence in related languages is a key concern of historical linguistics. In this paper we investigate semantic divergence across languages by measuring the semantic similarity of cognate sets in multiple languages. The method that we propose is based on cross-lingual word embeddings. 作者: allude 時間: 2025-3-26 12:43 作者: CRAMP 時間: 2025-3-26 17:14 作者: 類型 時間: 2025-3-27 00:04 作者: 錯 時間: 2025-3-27 03:38
,Grundzüge turbulenter Str?mungen,ons. We are the first to argue that these two important properties can play a major role in Chinese sentiment analysis. Hence, we learn phonetic features of Chinese characters and fuse them with their textual and visual features in order to mimic the way humans read and understand Chinese text. Expe作者: discord 時間: 2025-3-27 07:55
,Grundzüge turbulenter Str?mungen,eby seeking guidance and interacting with people of the community. The shared content, though informal and unstructured in nature, contains valuable medical and/or health related information and can be leveraged to produce structured suggestions to the common people. In this paper, at first we propo作者: 鐵塔等 時間: 2025-3-27 13:28
,Grundzüge turbulenter Str?mungen,nd the subjectivity of the user generated contents make the automatic “understanding” of texts extremely hard. Assuming that the semantic orientation of sentences is based on the manipulation of sentiment words, we built from scratch, for the Italian language, a network of local grammars for the ann作者: 整潔漂亮 時間: 2025-3-27 17:15 作者: 并入 時間: 2025-3-27 20:06 作者: TATE 時間: 2025-3-28 01:42 作者: 含水層 時間: 2025-3-28 04:29 作者: regale 時間: 2025-3-28 07:05 作者: heckle 時間: 2025-3-28 12:02 作者: Grating 時間: 2025-3-28 18:34 作者: Gossamer 時間: 2025-3-28 22:03
Opinion Spam Detection with?Attention-Based LSTM Networkse important features. This paper describes our approach to apply LSTM and attention-based mechanisms for detecting deceptive reviews. Experiments with the Three-domain data set [.] show that a BiLSTM model coupled with Multi-Headed Self Attention improves the F-measure from 81.49% to 87.59% in detecting fake reviews.作者: 窒息 時間: 2025-3-29 02:15 作者: 變白 時間: 2025-3-29 04:08
Kontinuumsbegriff und Kinematik,words effectively, we introduce root and entity tag embedding plus tensor layer to the neural networks. The effects of those are significant for improving NER model performance of MCLs. The proposed models outperform state-of-the-art including character-based approaches, and can be potentially applied to other morphologically complex languages.作者: Optic-Disk 時間: 2025-3-29 08:25
https://doi.org/10.1007/978-3-540-38441-0t uses character-based distributed representations to classify words into categories in the dictionary. The recognizer then uses the output of the classification as an additional feature. We conducted experiments to recognize named entities in recipe text and report the results to demonstrate the performance of our method.作者: 不能逃避 時間: 2025-3-29 14:56 作者: Acetabulum 時間: 2025-3-29 17:07
,Grundzüge turbulenter Str?mungen,rimental results on five different Chinese sentiment analysis datasets show that the inclusion of phonetic features significantly and consistently improves the performance of textual and visual representations.作者: 灌輸 時間: 2025-3-29 21:16 作者: MAIZE 時間: 2025-3-30 03:51 作者: –吃 時間: 2025-3-30 07:34 作者: 交響樂 時間: 2025-3-30 12:14
A Hybrid Generative/Discriminative Model for?Rapid Prototyping of?Domain-Specific Named Entity Recogetween NE chunks and non-NE words. It also allows a smooth transition to full-scale annotation because the discriminative model makes effective use of annotated data when available. Experiments involving two languages and three domains demonstrate that the proposed method outperforms baselines.作者: curriculum 時間: 2025-3-30 16:14 作者: 消瘦 時間: 2025-3-30 18:56 作者: 組裝 時間: 2025-3-30 23:12 作者: uveitis 時間: 2025-3-31 04:08 作者: 漂白 時間: 2025-3-31 05:21 作者: 碌碌之人 時間: 2025-3-31 09:41
Kontinuumsbegriff und Kinematik,ng to two independent translations of the same novel. The evaluation revealed that our proposed method based on the spectral norm could increase the accuracy compared to several baseline methods in both scenarios.
